Abstract:
Arabica coffee is a major cash crop in Namisindwa district particularly in Namabya Sub County however the yield of Arabica coffee is lower than the estimated quantity by Uganda Coffee Development Authority and little research has been done on determinants which affects productivity of Arabica coffee in Namisindwa District particularly in Namabya Sub County. The study was conducted in October and November 2023 assessing the determinants which affects productivity of Arabica coffee in Namisindwa District in Namabya Sub County. The study utilized random sampling technique to collect data from 80 households of Arabica coffee farmers who was interviewed using questionnaires with both structured and semi structured questions. Data was analyzed using scientific package for social scientists (SPSS version16.0). Descriptive statistics was used to analyze the characteristics of farmers as well as the years they have taken in producing Arabica coffee.
Parameters like age was expressed in terms of years of farmers who involve in Arabica coffee Production in Namabya Sub County. Sex was expressed in terms of the differences between men and women who involve in Arabica coffee production.
The percentage of both age and sex was obtained by dividing the number of farmers in each village with the total number of Arabica coffee farmers of the entire Sub County then multiplied by hundred. Models like regression models was used to analyze objective two. Multiple regression models were used because it shows one dependent variables being affected by the number of independent variables. Take for example of independent variables like economic determinants which included variables like price of inputs (x1, access to loansx2, availability of agro input shops x3 and farmers’ income x4). This was expressed in an equation as shown below. Y=x1, x2, x3, x4.... Meaning that dependent variable Y which is productivity of Arabica coffee depends on independentent variables x1, x2, x3, x4 and others. Descriptive and inferential statistics was used to analyze objective three. This involved the use of continuous variables like time to determine the period which farmers are being faced by low yield of Arabica coffee and how they have tried to solve the above problem of low yield of Arabica coffee in the Sub County.
